Salvatore Scognamiglio

University of Naples "Parthenope"

Post Doc Researcher

Department of Management and Quantitative Sciences

Italy

  • University of Naples "Parthenope"

SCHOLARLY PAPERS

5

DOWNLOADS
Rank 40,200

SSRN RANKINGS

Top 40,200

in Total Papers Downloads

2,437

SSRN CITATIONS
Rank 48,899

SSRN RANKINGS

Top 48,899

in Total Papers Citations

14

CROSSREF CITATIONS

4

Scholarly Papers (5)

Actions:
Email selected abstracts
1.

Time-Series Forecasting of Mortality Rates using Deep Learning

Number of pages: 26 Posted: 04 Jun 2020
Francesca Perla, Ronald Richman, Salvatore Scognamiglio and Mario V. Wuthrich
University of Naples Parthenope - Department of Management Studies and Quantitative Methods, Old Mutual Insure, University of Naples "Parthenope" and RiskLab, ETH Zurich
Downloads 1,064 (41,046)
Citation 16

Abstract:

Loading...

Mortality Forecasting, Recurrent Neural Networks, Convolutional Neural Networks, Representation Learning, Time-Series Forecasting, Lee Carter Model, Human Mortality Database

2.

An Investigation of Machine Learning Approaches in the Solvency II Valuation Framework

Number of pages: 25 Posted: 03 Jan 2019
Gilberto Castellani, Ugo Fiore, Zelda Marino, Luca Passalacqua, Francesca Perla, Salvatore Scognamiglio and Paolo Zanetti
Sapienza University of Rome, University of Naples Parthenope - Department of Management Studies and Quantitative Methods, University of Naples Parthenope - Department of Management Studies and Quantitative Methods, La Sapienza, University of Rome, University of Naples Parthenope - Department of Management Studies and Quantitative Methods, University of Naples "Parthenope" and University of Naples Parthenope - Department of Management Studies and Quantitative Methods
Downloads 839 (57,250)
Citation 9

Abstract:

Loading...

Solvency II, Nested Monte Carlo, With-Profit Insurance Policies, Least Squares Monte Carlo, Support Vector Machines, Deep Learning

3.

Accurate and Explainable Mortality Forecasting with the LocalGLMnet

Number of pages: 27 Posted: 10 Mar 2023
Francesca Perla, Ronald Richman, Salvatore Scognamiglio and Mario V. Wuthrich
University of Naples Parthenope - Department of Management Studies and Quantitative Methods, Old Mutual Insure, University of Naples "Parthenope" and RiskLab, ETH Zurich
Downloads 350 (166,608)

Abstract:

Loading...

Mortality forecasting, explainable deep learning, neural networks, Lee–Carter model, multi-population mortality model, Human Mortality Database, LocalGLMnet

4.

Calibrating the Lee-Carter and the Poisson Lee-Carter Models Via Neural Networks

Number of pages: 32 Posted: 28 Jun 2021
Salvatore Scognamiglio
University of Naples "Parthenope"
Downloads 122 (440,846)
Citation 5

Abstract:

Loading...

Mortality modeling, Multi-population mortality modeling. neural networks, Lee-Carter model, Human Mortality Database

5.

Robust Classification via Support Vector Machines

Downloads 62 (670,769)
Citation 1

Robust Classification via Support Vector Machines

Number of pages: 27 Posted: 29 Apr 2021 Last Revised: 01 Mar 2022
Alexandru Vali Asimit, Ioannis Kyriakou, Simone Santoni, Salvatore Scognamiglio and Rui Zhu
City University London - The Business School, Bayes Business School (formerly Cass), City, University of London, University of Bologna - Department of Management, University of Naples "Parthenope" and City University London
Downloads 43 (806,167)
Citation 2

Abstract:

Loading...

support vector machine, robust classification, data uncertainty, extreme empirical loss

Robust Classification Via Support Vector Machines

Number of pages: 27 Posted: 04 Apr 2022
Alexandru Vali Asimit, Ioannis Kyriakou, Simone Santoni, Salvatore Scognamiglio and Rui Zhu
City University London - The Business School, Bayes Business School (formerly Cass), City, University of London, affiliation not provided to SSRN, University of Naples "Parthenope" and affiliation not provided to SSRN
Downloads 19 (1,030,527)
Citation 2

Abstract:

Loading...

Binary robust classification, insurance fraud prediction, mortgage lending prediction, support vector machine